Local learning rules have been explored since Donald Hebb proposed a simple model for learning in the brain [1]}. The main advantage of this kind of learning algorithm is requiring lower memory resources. Some works are biologically inspired [2]}, [3]}, while others focus solely on efficiency [4]}, [5]}. There is a growing body of work discussing whether the brain does backpropagation [6]}, [7]}, with some approximations for training artificial neural networks [8]}, [9]}, [10]}.
